Introduction:

Real-time mobility data from Wuhan, China, and detailed case data, including travel history, was of vital importance for the control of COVID-19, in order to determine the impact of control measures.

Objective:

To analyze the cases reported in the five most affected regions by COVID-19 in Peru, and its correlation with mobility data.

Method:

Data of the confirmed cases of COVID-19 obtained from the Centro Nacional de Epidemiologia, Prevención y Control de Enfermedades de Perú (National Center for Epidemiology, Prevention and Control of Diseases of Peru) (https://www.dge.gob.pe/) in the period from 6 From March until August 17, 2020 were included; and the regions with the highest number of cases (CDC-Peru) (Arequipa, Callao, Lima, Lambayeque and Piura) were selected. The mobility data was obtained from the Local Mobility Reports (Community Mobility Reports-Google Mobility Reports) (https://www.google.com/covid19/mobility/) of Peru and downloaded in a CSV file. The categories included in the mobility reports were: retail stores and leisure, public transport stations, workplaces and residential areas.

Results:

165 data found in Google Mobility Reports were analyzed; these having a daily data frequency. The same amount of data was obtained from the CDC-Peru. A drop was observed in all places studied except for residential areas in the country. Regarding associations, a negative correlation was found only in residential areas.

Conclusion:

There was a reduction in mobility due to quarantine, and staying at home is a factor to avoid infections.

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